BIFIE.mva: Missing Value Analysis

In BIFIEsurvey: Tools for Survey Statistics in Educational Assessment

Missing Value Analysis

Description

Conducts a missing value analysis.

Usage

BIFIE.mva( BIFIEobj, missvars, covariates=NULL, se=TRUE )

## S3 method for class 'BIFIE.mva'
summary(object,digits=4,...)

Arguments

BIFIEobj	Object of class BIFIEdata
missvars	Vector of variables for which missing value statistics should be computed
covariates	Vector of variables which work as covariates
se	Optional logical indicating whether statistical inference based on replication should be employed.
object	Object of class BIFIE.correl
digits	Number of digits for rounding output
...	Further arguments to be passed

Value

A list with following entries

stat.mva	Data frame with missing value statistics
res_list	List with extensive output split according to each variable in missvars
...	More values

Examples

#############################################################################
# EXAMPLE 1: Imputed TIMSS dataset
#############################################################################

data(data.timss1)
data(data.timssrep)

# create BIFIE.dat object
BIFIEdata <- BIFIEsurvey::BIFIE.data( data.list=data.timss1,
                wgt=data.timss1[[1]]$TOTWGT, wgtrep=data.timssrep[, -1 ] )

# missing value analysis for "scsci" and "books" and three covariates
res1 <- BIFIEsurvey::BIFIE.mva( BIFIEdata, missvars=c("scsci", "books" ),
             covariates=c("ASMMAT", "female", "ASSSCI") )
summary(res1)

# missing value analysis without statistical inference and without covariates
res2 <- BIFIEsurvey::BIFIE.mva( BIFIEdata, missvars=c("scsci", "books"), se=FALSE)
summary(res2)

BIFIEsurvey documentation built on May 29, 2024, 2:52 a.m.